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Chaotic Logic -- Copyright Plenum Press © 1994 |
We are surrounded by complex systems; they touch every aspect of our lives. Our bodies, minds, and environments are all incredibly, perhaps incomprehensibly, complex. And yet, until very recently, there has never been anything close to a science of complex systems.
Mainstream "simple-systems" science can give us dazzling details about the structure and function of our cells, molecules and atoms; and it can explain for us the flickerings and motions of objects so distant that it would take millions of years to reach them. It can help us cure diseases, and instruct us how to build computers, bridges, cars, airplanes, houses, nuclear weapons, precision surgical tools, et cetera et cetera.
But virtually all of these achievements were arrived at by the same "meta-method": study a complex phenomenon by
1) breaking it down into its component parts
2) studying the component parts
3) using information about the component parts to obtain information about the whole.
This method, often called "reductionism", does not seem to work very well for studying complex, self-organizing phenomena. It would seem that something beyond reductionism is needed, some new methodology better suited to complex systems.
This observation was the raison d'etre of the mid-century cybernetics/ general systems theory movement. And it is the focal point of an increasing amount of contemporary research: in physics, in biology, in computer science, in psychology, in chemistry,.... We have no completely general theory of complex system dynamics, but we have a wealth of interesting details and moderately general insights. The theory of chaotic dynamical systems hasgiven us a fairly good understanding of phenomena like weather, heartbeats, and smell. By putting together neural network theory, dynamical systems theory and information theory, we can begin to understand significant aspects of the mind and brain. By synthesizing insights from mathematics, biology and physics, we can begin to understand biological evolution.
My goal in writing this book was see whether, by combining current ideas regarding complex system dynamics with the pattern-theoretic psychology developed in my earlier books, it might not be possible to work out a dynamics of mind. This is, everyone will agree, a task at which reductionist science has utterly failed.
We began, if you recall, with four "intuitive equations":
Linguistic system = syntactic system + semantic system
Belief system = linguistic system + self-generating system
Mind = dual network + belief systems
Reality = minds + shared belief system
Now we are in a position to understand how much, and how little, these system-defining equations reveal. The cognitive equation gives the flow of mind, and these equations describe attractors which direct this flow. To take the "flow" metaphor one step further, the system-defining equations are something like complexly-contoured continents, guiding the flow of the vast chaotic ocean that is pattern space. But yet they are not quite like continents, because they are themselves formed from the flow of the ocean itself.
As emphasized throughout, all this is only a beginning. We have considered a decent number of concrete examples -- but not enough. The abstract ideas given here must be fleshed out by further contact with the nitty-gritty details of real languages, real trains of thought, real cultures, real belief systems, real personalities, real subjective realities.
However, I do feel that some genuine insight has been gained. Previously uncharted regions have been tentatively explored. The first few steps have been taken toward understanding that most mysterious and most essential process by which logic interfaces with self-organizing habit ... by which order synergizes with chaos to form the complex patterns of becoming that we call -- mind.